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This collection of layers includes summary statistics from input and output data used for simulation of vegetation response to climate change in California. The historical data layers represent the 30 year period from 1961 to 1990. Future data layers represent each four 20 year periods: 2010-2029, 2030-2049, 2060-2079, and 2080-2099. The simulations were performed using MC1 dynamic global vegetation model (DGVM), source code revision 152. The model was parameterized and evaluated by the DGVM research group at the US Forest Service Pacific Northwest Research Station, with support from the Western Wildland Environmental Threat Assessment Center. The model was parameterized to maximize concordance with maps of potential...
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This collection of layers includes summary statistics from input and output data used for simulation of vegetation response to climate change in California. The historical data layers represent the 30 year period from 1961 to 1990. Future data layers represent each four 20 year periods: 2010-2029, 2030-2049, 2060-2079, and 2080-2099. The simulations were performed using MC1 dynamic global vegetation model (DGVM), source code revision 152. The model was parameterized and evaluated by the DGVM research group at the US Forest Service Pacific Northwest Research Station, with support from the Western Wildland Environmental Threat Assessment Center. The model was parameterized to maximize concordance with maps of potential...
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Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.
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The Geographic Names Information System (GNIS) is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types.
Tags: Adair, Allen, Anderson, Antarctica, Antarctica, All tags...
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This collection of layers includes summary statistics from input and output data used for simulation of vegetation response to climate change in California. The historical data layers represent the 30 year period from 1961 to 1990. Future data layers represent each four 20 year periods: 2010-2029, 2030-2049, 2060-2079, and 2080-2099. The simulations were performed using MC1 dynamic global vegetation model (DGVM), source code revision 152. The model was parameterized and evaluated by the DGVM research group at the US Forest Service Pacific Northwest Research Station, with support from the Western Wildland Environmental Threat Assessment Center. The model was parameterized to maximize concordance with maps of potential...
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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Geospatial data is comprised of government boundaries.
Tags: Adair, Allen, Anderson, Ballard, Barren, All tags...
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This collection of layers includes summary statistics from input and output data used for simulation of vegetation response to climate change in California. The historical data layers represent the 30 year period from 1961 to 1990. Future data layers represent each four 20 year periods: 2010-2029, 2030-2049, 2060-2079, and 2080-2099. The simulations were performed using MC1 dynamic global vegetation model (DGVM), source code revision 152. The model was parameterized and evaluated by the DGVM research group at the US Forest Service Pacific Northwest Research Station, with support from the Western Wildland Environmental Threat Assessment Center. The model was parameterized to maximize concordance with maps of potential...
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.


map background search result map search result map Forecast Barren Land Extent Under GFDL B1 Scenario, 2060-2079 Forecast Barren Land Extent Under GFDL A2 Scenario, 2080-2099 Forecast Barren Land Extent Under PCM A2 Scenario, 2080-2099 Forecast Barren Land Extent Under PCM A2 Scenario, 2010-2029 FSA 10:1 NAIP Imagery m_3608502_sw_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608509_ne_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608608_ne_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608616_nw_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708557_se_16_h_20160519_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708558_nw_16_h_20160522_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708664_ne_16_h_20160519_20160913 3.75 x 3.75 minute JPEG2000 from The National Map USGS US Topo 7.5-minute map for Glasgow North, KY 2010 USGS US Topo 7.5-minute map for Glasgow South, KY 2013 USGS US Topo 7.5-minute map for Lucas, KY 2010 USGS US Topo 7.5-minute map for Mammoth Cave, KY 2013 USGS US Topo 7.5-minute map for Meador, KY 2016 USGS US Topo 7.5-minute map for Smiths Grove, KY 2016 USGS US Topo 7.5-minute map for Sulphur Lick, KY 2013 USGS National Boundary Dataset (NBD) in Kentucky State or Territory (published 20230923) GeoPackage Geographic Names Information System (GNIS) Domestic Names for KY (published 20230801) pipes FSA 10:1 NAIP Imagery m_3608502_sw_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608509_ne_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608608_ne_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3608616_nw_16_h_20160523_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708557_se_16_h_20160519_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708558_nw_16_h_20160522_20160913 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3708664_ne_16_h_20160519_20160913 3.75 x 3.75 minute JPEG2000 from The National Map USGS US Topo 7.5-minute map for Glasgow North, KY 2010 USGS US Topo 7.5-minute map for Glasgow South, KY 2013 USGS US Topo 7.5-minute map for Lucas, KY 2010 USGS US Topo 7.5-minute map for Mammoth Cave, KY 2013 USGS US Topo 7.5-minute map for Meador, KY 2016 USGS US Topo 7.5-minute map for Smiths Grove, KY 2016 USGS US Topo 7.5-minute map for Sulphur Lick, KY 2013 USGS National Boundary Dataset (NBD) in Kentucky State or Territory (published 20230923) GeoPackage Geographic Names Information System (GNIS) Domestic Names for KY (published 20230801) pipes Forecast Barren Land Extent Under GFDL B1 Scenario, 2060-2079 Forecast Barren Land Extent Under GFDL A2 Scenario, 2080-2099 Forecast Barren Land Extent Under PCM A2 Scenario, 2080-2099 Forecast Barren Land Extent Under PCM A2 Scenario, 2010-2029